Publikationen: Forschungsgruppe Media Computing – FHSTP

Iber, M., Dumphart, B., Oliveira, V. A. de. J., Ferstl, S., Reis, J., Slijepcevic, D., Heller, M., Raberger, A.-M., & Horsak, B. (2021). Mind the Steps: Towards Auditory Feedback in Tele-Rehabilitation Based on Automated Gait Classification. In Proceedings of the 16th International Audio Mostly Conference (AM"21). Audio Mostly 2021. https://doi.org/10/gnt2tc

Bibtex

Krondorfer, P., Slijepčević, D., Unglaube, F., Kranzl, A., Breiteneder, C., Zeppelzauer, M., & Horsak, B. (2021). Deep learning-based similarity retrieval in clinical 3D gait analysis. Gait & Posture, 90, 127–128. https://doi.org/https://doi.org/10.1016/j.gaitpost.2021.09.066

Slijepčević, D., Henzl, M., Klausner, L. D., Dam, T., Kieseberg, P., & Zeppelzauer, M. (2021). k‑Anonymity in Practice: How Generalisation and Suppression Affect Machine Learning Classifiers. Computers & Security, 111, 19. https://doi.org/10.1016/j.cose.2021.102488

Zielinski, B., Lipinski, M., Juda, M., Zeppelzauer, Matthias, & Dlotko, Pawel. (2021). Persistence Codebooks for Topological Data Analysis. Journal of Artificial Intelligence Review, 54, 1969–2009. https://doi.org/https://doi.org/10.1007/s10462-020-09897-4

Horsak, B., Slijepcevic, D., Raberger, A.-M., Schwab, C., Worisch, M., & Zeppelzauer, M. (2020). GaitRec, a large-scale ground reaction force dataset of healthy and impaired gait. Scientific Data, 7:143(1), 1–8. https://doi.org/10/gh372d

Horsak, B., Dumphart, B., Slijepcevic, D., & Zeppelzauer, M. (2020). Explainable Artificial Intelligence (XAI) und ihre Anwendung auf Klassifikationsprobleme in der Ganganalyse. Abstractband Des 3. GAMMA Kongress. 3. GAMMA Kongress, München, Deutschland.

Bibtex

Horst, F., Slijepcevic, D., Zeppelzauer, M., Raberger, A. M., Lapuschkin, S., Samek, W., Schöllhorn, W. I., Breiteneder, C., & Horsak, B. (2020). Explaining automated gender classification of human gait. Gait & Posture, 81, supplement 1, 159–160. https://doi.org/10/ghr9k6

Iber, M., Lechner, P., Jandl, C., Mader, M., & Reichmann, M. (2020). Auditory augmented process monitoring for cyber physical production systems. Personal and Ubiquitous Computing. https://doi.org/10/ghz24q

Slijepcevic, D., Zeppelzauer, M., Schwab, Caterine, Raberger, A.-M., Breitender, C., & Horsak, B. (2020). Input Representations and Classification Strategies for Automated Human Gait Analysis. Gait & Posture, 76, 198–203. https://doi.org/10/ghz24x

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Despotovic, M., Koch, D., Leiber, S., Döller, M., Sakeena, M., & Zeppelzauer, M. (2019). Prediction and analysis of heating energy demand for detached houses by computer vision. Energy & Buildings, 193, 29–35. https://doi.org/10/fsxn

Iber, M., Lechner, P., Jandl, C., Mader, M., & Reichmann, M. (2019). Auditory Augmented Reality for Cyber Physical Production Systems. AudioMostly (AM"19). AudioMostly (AM"19), Nottingham, UNited Kingdom. https://doi.org/10.1145/3356590.3356600}

Bibtex

Seidl, Markus, & Zeppelzauer, Matthias. (2019). Towards Distinction of Rock Art Pecking Styles with a Hybrid 2D/3D Approach. Proceedings of the International Conference on Content-Based Multimedia Indexing (CBMI), 4.

Bibtex

Slijepcevic, D., Raberger, A.-M., Zeppelzauer, M., Dumphart, B., Breiteneder, C., & Horsak, B. (2019). On the usefulness of statistical parameter mapping for feature selection in automated gait classification. Book of Abstracts of the 25th Conference of the European Society of Biomechanics (ESB), 1.

Bibtex

Slijepcevic, D., Raberger, A.-M., Zeppelzauer, M., Dumphart, B., Breiteneder, C., & Horsak, B. (2019). On the usefullness of statistical parameter mapping for feature selection in automated gait classification. Book of Abstracts of the 25th Conference of the European Society of Biomechanics (ESB), 1.

Bibtex

Stoiber, C., Rind, A., Grassinger, F., Gutounig, R., Goldgruber, E., Sedlmair, M., Emrich, S., & Aigner, W. (2019). netflower: Dynamic Network Visualization for Data Journalists. Computer Graphics Forum (EuroVis "19), 38. https://doi.org/10/ghm4jz

Zielinski, B., Lipinski, Michal, Juda, M., Zeppelzauer, M., & Dlotko, Pawel. (2019). Persistence Bag-of-Words for Topological Data Analysis. Proceedings of the International Joint Conference on Artificial Intelligence 2019, 6. https://doi.org/10/ghpp7z

Andrienko, N., Lammarsch, T., Andrienko, G., Fuchs, G., Keim, D. A., Miksch, S., & Rind, A. (2018). Viewing Visual Analytics as Model Building. Computer Graphics Forum, 37(6), 275–299. https://doi.org/10/gdv9s7

Bernard, J., Zeppelzauer, M., Sedlmair, M., & Aigner, W. (2018). VIAL – A Unified Process for Visual-Interactive Labeling. The Visual Computer, 34(1189), 16. https://doi.org/10/gd5hr3

Bernard, J., Zeppelzauer, M., Lehmann, M., Müller, M., & Sedlmair, M. (2018). Towards User-Centered Active Learning Algorithms. Computer Graphics Forum, 37, 121–132. https://doi.org/10/gdw79h

Luh, R., Schramm, G., Wagner, M., Janicke, H., & Schrittwieser, S. (2018). SEQUIN: a grammar inference framework for analyzing malicious system behavior. Journal of Computer Virology and Hacking Techniques, 01–21. https://doi.org/10/cwdf